Climatological studies of lapse rates during summer months vis-à-vis All India Summer Monsoon Rainfall

The combined mean normal lapse rates for 0000 and 1200 UTC for 35 Radiosonde (RS) stations based on the period 1971-99 during the summer months (March to May) were worked out for standard levels and analysed. To know whether any relationship exists between the distribution of summer lapse rates and the all India summer monsoon rainfall (June to September), the mean lapse rates for three good monsoon years and six deficient years during the same period were worked out separately and the Lapse Rate Anomalies (LRAs) were examined in detail. In excessive monsoon rainfall years the LRAs were generally negative (instable atmosphere) during summer months (March-May) in the lower and middle troposphere and the anomalies were positive in the upper troposphere. In the deficient monsoon years, the case is reverse i.e., LRAs were positive in the lower troposphere (inhibiting the convective activity) while they were negative in the middle and upper troposphere. The same results were noticed in the recent worst monsoon year 2002 and bad monsoon year 2004. The LRAs thus give signals in the months of March to May regarding the ensuing monsoon rainfall qualitatively and can be used as one of the tools for long range forecasting.

Drone measurements of surface-based winter temperature inversions in the High Arctic at Eureka

The absence of sunlight during the winter in the High Arctic results in a strong surface-based atmospheric temperature inversion, especially during clear skies and light surface wind conditions. The inversion suppresses turbulent heat transfer between the ground and the boundary layer. As a result, the difference between the surface air temperature, measured at a height of 2 m, and the ground skin temperature can exceed several degrees Celsius. Such inversions occur very frequently in polar regions, are of interest to understand the mechanisms responsible for surface–atmosphere heat, mass, and momentum exchanges, and are critical for satellite validation studies. In this paper we present the results of operations of two commercial remotely piloted aircraft systems, or drones, at the Polar Environment Atmospheric Research Laboratory, Eureka, Nunavut, Canada, at 80∘ N latitude. The drones are the Matrice 100 and Matrice 210 RTK quadcopters manufactured by DJI and were flown over Eureka during the February–March field campaigns in 2017 and 2020. They were equipped with a temperature measurement system built on a Raspberry Pi single-board computer, three platinum-wire temperature sensors, a Global Navigation Satellite System receiver, and a barometric altimeter. We demonstrate that the drones can be effectively used in the extremely challenging High Arctic conditions to measure vertical temperature profiles up to 75 m above the ground and sea ice surface at ambient temperatures down to −46 ∘C. Our results indicate that the inversion lapse rates within the 0–10 m altitude range above the ground can reach values of ∼ 10–30 ∘C(100m)-1 (∼ 100–300 ∘Ckm-1). The results are in good agreement with the coincident surface air temperatures measured at 2, 6, and 10 m levels at the National Oceanic and Atmospheric Administration flux tower at the Polar Environment Atmospheric Research Laboratory. Above 10 m more gradual inversion with order-of-magnitude smaller lapse rates is recorded by the drone. This inversion lapse rate agrees well with the results obtained from the radiosonde temperature measurements. Above the sea ice drone temperature profiles are found to have an isothermal layer above a surface-based layer of instability, which is attributed to the heat flux through the sea ice. With the drones we were able to evaluate the influence of local topography on the surface-based inversion structure above the ground and to measure extremely cold temperatures of air that can pool in topographic depressions. The unique technical challenges of conducting drone campaigns in the winter High Arctic are highlighted in the paper.

Quantifying energy balance regimes in the modern climate, their link to lapse rate regimes, and their response to warming

Energy balance and lapse rate regimes qualitatively characterize the low, mid, and high latitudes of Earth’s modern climate. Currently we do not have a complete quantitative understanding of the spatio-temporal structure of energy balance regimes (e.g., Radiative Convective Equilibrium, RCE, and Radiative Advective Equilibrium, RAE) and their connection to lapse rate regimes (moist adiabat and surface inversion). Here we use the vertically-integrated moist static energy budget to define a nondimensional number that quantifies where and when RCE and RAE are approximately satisfied in Earth’s modern climate. We find RCE exists yearround in the tropics and in theNorthern midlatitudes during summertime. RAE exists yearround over Antarctica and in the Arctic with the exception of early summer. We show lapse rates in RCE and RAE are consistent with moist adiabatic and surface inversion lapse rates, respectively. We use idealized models (energy balance and aquaplanet) to test the following hypotheses: 1) RCE occurs during midlatitude summer for land-like (small heat capacity) surface conditions and 2) sea ice is necessary for the existence of annual-mean RAE over a polar ocean, such as the Arctic. Consistent with 1), an aquaplanet configured with a shallow mixed layer transitions to RCE in the midlatitudes during summertime whereas it does not for a deep mixed layer. Furthermore, we confirm 2) using mechanism-denial aquaplanet experiments with and without thermodynamic sea ice. Finally, we show energy balance regimes of the modern climate provide a useful guide to the vertical structure of the warming response in the annual mean, and seasonally over the tropics and the Southern high latitudes.

Variations of Tropical Lapse Rates in Climate Models and their Implications for Upper Tropospheric Warming

The vertical temperature structure in the tropics is primarily set by convection and therefore follows a moist adiabat to first order. However, tropical upper tropospheric temperatures differ among climate models and observations, as atmospheric convection remains poorly understood. Here, we quantify the variations in tropical lapse rates in CMIP6 models and explore reasons for these variations. We find that differences in surface temperatures weighted by the regions of strongest convection cannot explain these variations and therefore we hypothesise that the representation of convection itself and associated small scale processes are responsible. We reproduce these variations in perturbed physics experiments with the global atmospheric model ICON-A, in which we vary autoconversion and entrainment parameters. For smaller autoconversion values, additional freezing enthalpy from the cloud water that is not precipitated warms the upper troposphere. Smaller entrainment rates also lead to a warmer upper troposphere, as convection and thus latent heating reaches higher. Furthermore, we show that according to most radiosonde datasets all CMIP6 AMIP simulations overestimate recent upper tropospheric warming. Additionally, all radiosonde datasets agree that climate models on average overestimate the amount of upper tropospheric warming for a given lower tropospheric warming. We demonstrate that increased entrainment rates reduce this overestimation, likely because of the reduction of latent heat release in the upper troposphere. Our results suggest that imperfect convection parameterisations are responsible for a considerable part of the variations in tropical lapse rates and also part of the overestimation of warming compared to the observations.

Individualized Assays of Temporal Coding in the Ascending Human Auditory System

Neural phase-locking to temporal fluctuations is a fundamental and unique mechanism by which acoustic information is encoded by the auditory system. The perceptual role of this metabolically expensive mechanism, the neural phase-locking to temporal fine structure (TFS) in particular, is debated. Although hypothesized, it is unclear if auditory perceptual deficits in certain clinical populations are attributable to deficits in TFS coding. Efforts to uncover the role of TFS have been impeded by the fact that there are no established assays for quantifying the fidelity of TFS coding at the individual level. While many candidates have been proposed, for an assay to be useful, it should not only intrinsically depend on TFS coding, but should also have the property that individual differences in the assay reflect TFS coding per se over and beyond other sources of variance. Here, we evaluate a range of behavioral and electroencephalogram (EEG)-based measures as candidate individualized measures of TFS sensitivity. Our comparisons of behavioral and EEG-based metrics suggest that extraneous variables dominate both behavioral scores and EEG amplitude metrics, rendering them ineffective. After adjusting behavioral scores using lapse rates, and extracting latency or percent-growth metrics from EEG, interaural timing sensitivity measures exhibit robust behavior-EEG correlations. Together with the fact that unambiguous theoretical links can be made relating binaural measures and phase-locking to TFS, our results suggest that these "adjusted" binaural assays may be well-suited for quantifying individual TFS processing.

Spectrum of Near-Storm Environments for Significant Severe Right-Moving Supercells in the Contiguous United States

Proximity soundings have long been used to explore how the vertical structure of temperature, humidity, and winds influence convective storms and their associated hazards. In severe thunderstorm research and forecasting, convective parameters are often used to summarize certain characteristics of the sounding. While extremely useful, these parameters are unable to describe the rich complexity that is readily apparent in hodographs and skew-T diagrams. Motivated by a desire to retain more of these details, the present study uses self-organizing maps (SOMs) to group soundings based on their full vertical structure. The analysis makes use of a sample of more than 10,000 model proximity soundings for right-moving supercells associated with tornadoes and significant severe hail and straight-line winds in the Contiguous United States (CONUS). Separate SOMs are developed for the wind and thermodynamic profiles, each with 3×3 nodes, resulting in a set of nine hodographs and nine skew-T diagrams that broadly represent the spectrum of near-storm environments for significant severe right-moving supercells in the CONUS. Both SOMs are shown to provide a good representation of the variability in key convective parameters, although, for the thermodynamic SOM, variations in LCL heights and mid-level lapse rates are somewhat limited. Based on the soundings assigned to them, the SOM nodes are characterized in terms of their associated hazards, their relationship with storm mode and mesocyclone strength, and their spatial and temporal variability. Potential applications of the SOMs in severe weather forecasting and idealized numerical simulations are also highlighted.

Rise of the Colorado Plateau: A Synthesis of Paleoelevation Constraints From the Region and a Path Forward Using Temperature-Based Elevation Proxies

The Colorado Plateau’s complex landscape has motivated over a century of debate, key to which is understanding the timing and processes of surface uplift of the greater Colorado Plateau region, and its interactions with erosion, drainage reorganization, and landscape evolution. Here, we evaluate what is known about the surface uplift history from prior paleoelevation estimates from the region by synthesizing and evaluating estimates 1) in context inferred from geologic, geomorphic, and thermochronologic constraints, and 2) in light of recent isotopic and paleobotanical proxy method advancements. Altogether, existing data and estimates suggest that half-modern surface elevations were attained by the end of the Laramide orogeny (∼40 Ma), and near-modern surface elevations by the mid-Miocene (∼16 Ma). However, our analysis of paleoelevation proxy methods highlights the need to improve proxy estimates from carbonate and floral archives including the ∼6–16 Ma Bidahochi and ∼34 Ma Florissant Formations and explore understudied (with respect to paleoelevation) Laramide basin deposits to fill knowledge gaps. We argue that there are opportunities to leverage recent advancements in temperature-based paleoaltimetry to refine the surface uplift history; for instance, via systematic comparison of clumped isotope and paleobotanical thermometry methods applied to lacustrine carbonates that span the region in both space and time, and by use of paleoclimate model mediated lapse rates in paleoelevation reconstruction.

The Precipitation Imaging Package: Phase Partitioning Capabilities

Surface precipitation phase is a fundamental meteorological property with immense importance. Accurate classification of phase from satellite remotely sensed observations is difficult. This study demonstrates the ability of the Precipitation Imaging Package (PIP), a ground-based, in situ precipitation imager, to distinguish precipitation phase. The PIP precipitation phase identification capabilities are compared to observer records from the National Weather Service (NWS) office in Marquette, Michigan, as well as co-located observations from profiling and scanning radars, disdrometer data, and surface meteorological measurements. Examined are 13 events with at least one precipitation phase transition. The PIP-determined onsets and endings of the respective precipitation phase periods agree to within 15 min of NWS observer records for the vast majority of the events. Additionally, the PIP and NWS liquid water equivalent accumulations for 12 of the 13 events were within 10%. Co-located observations from scanning and profiling radars, as well as reanalysis-derived synoptic and thermodynamic conditions, support the accuracy of the precipitation phases identified by the PIP. PIP observations for the phase transition events are compared to output from a parameterization based on wet bulb and near-surface lapse rates to produce a probability of solid precipitation. The PIP phase identification and the parameterization output are consistent. This work highlights the ability of the PIP to properly characterize hydrometeor phase and provide dependable precipitation accumulations under complicated mixed-phase and rain and snow (or vice versa) transition events.

Radar-Based Comparison of Thunderstorm Outflow Boundary Speeds versus Peak Wind Gusts from Automated Stations

Straight-line winds are arguably the most challenging element considered by operational forecasters when issuing severe thunderstorm warnings. Determining the potential maximum surface wind gust prior to an observed, measured gust is very difficult. This work builds upon prior research that quantified a relationship between the observed outflow boundary speed and corresponding measured wind gusts. Though this prior study was limited to a 30-case dataset over eastern Colorado, the current study comprises 943 cases across the contiguous United States and encompasses all times of day, seasons, and regions while representing various convective modes and associated near-storm environments.The wind gust ratios (WGRs), or the ratio between a measured wind gust and the associated outflow boundary speed, had a nationwide median of 1.44, mean of 1.68, and 25th–75th percentiles of 1.19–1.91, respectively. WGRs varied considerably by region, season, time of day, convective mode, near-storm environment, and outflow boundary speed. WGRs tended to be higher in the plains, Intermountain West, and southern coastal regions, lower in the cool season and during the morning and overnight, and lower in linear convective modes compared to supercell and disorganized modes. Environments with stronger mean winds and low-to-midlevel shear vector magnitudes tended to have lower WGRs, while those with steeper low-level lapse rates and other thermodynamic characteristics favorable for momentum transfer and evaporative cooling tended to have higher WGRs. As outflow boundary speed increases, WGRs—and their variability—decreases. Applying these findings may help operational meteorologists provide more accurate severe thunderstorm warnings.